Organic Contaminants in Canadian Municipal Sewage Sludge. Part II. Persistent Chlorinated Compounds and Polycyclic Aromatic Hydrocarbons
Bibliographic record
Abstract
Abstract Thirty-five sewage sludge samples collected across Canada were analyzed for 18 polycyclic aromatic hydrocarbons (PAHs), 17 congeners of polychlorinated biphenyls (PCBs) and seven selected chlorinated compounds. Samples were prepared by accelerated solvent extraction and standard column cleanup procedures using silica gel and Florisil. Gas chromatography with electron-capture detection was used for the determination of PCBs. Gas chromatography/mass spectrometry with electron-impact ionization and methane negative ion chemical ionization were used for the detection of PAHs and the chlorinated compounds, respectively. PAHs were detected in nearly all samples, with a total concentration ranging from 0.14 to 209 µg/g (median 3.65 µg/g) on a dry weight basis. Phenanthrene, fluoranthene and pyrene were present at the highest concentrations, with medians ranging from 0.56 to 0.58 µg/g. PCBs were also found in all samples, with a total PCB concentration ranging from 31 to 323 ng/g. The most abundant PCBs (congeners 52, 101 and 110) had median concentrations of 12 ng/g or above. While pentachlorobenzene and hexachlorobenzene were observed in all sludge, at low ng/g levels, no other less chlorinated benzenes have been detected in the same samples. Octachlorostyrene was only found in the Ontario samples, with concentrations ranging from 0.3 to 11.5 ng/g (median 0.9 ng/g). For the chlorinated insecticides, only p,p'-DDE, α- and γ-chlordane were found on a more regular basis, with median concentrations of 12.0, 0.4 and 0.8 ng/g, respectively. These results suggest that the above toxic chemicals are occurring in Canadian sewage samples and are persistent enough to survive the existing sewage treatment processes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".